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» Modelling decision making with probabilistic causation
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AAAI
2008
13 years 10 months ago
Maximum Entropy Inverse Reinforcement Learning
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
CLUSTER
2008
IEEE
14 years 2 months ago
Empirical-based probabilistic upper bounds for urgent computing applications
—Scientific simulation and modeling often aid in making critical decisions in such diverse fields as city planning, severe weather prediction and influenza modeling. In some o...
Nick Trebon, Peter H. Beckman
UM
2005
Springer
14 years 1 months ago
Bayesphone: Precomputation of Context-Sensitive Policies for Inquiry and Action in Mobile Devices
Inference and decision making with probabilistic user models may be infeasible on portable devices such as cell phones. We highlight the opportunity for storing and using precomput...
Eric Horvitz, Paul Koch, Raman Sarin, Johnson Apac...
ECCV
2002
Springer
14 years 9 months ago
Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
This paper describes techniques for fusing the output of multiple cues to robustly and accurately segment foreground objects from the background in image sequences. Two different m...
Eric Hayman, Jan-Olof Eklundh
ECAI
2008
Springer
13 years 9 months ago
A probabilistic analysis of diagnosability in discrete event systems
Abstract. This paper shows that we can take advantage of information about the probabilities of the occurrences of events, when this information is available, to refine the classic...
Farid Nouioua, Philippe Dague